Evidence map›Paper›PMID 37931192›Full record

ArticleHealth affairs (Project Hope)2023

No Improvement In Mental Health Treatment Or Patient-Reported Outcomes At Medicare ACOs For Depression And Anxiety Disorders.

Jason M Hockenberry, Hefei Wen, Benjamin G Druss, Travis Loux, Kenton J Johnston

Erratum issuedAbstract read
In one paragraph

Article in Health affairs (Project Hope), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Jason M HockenberryJason M. Hockenberry, Yale University, New Haven, Connecticut.
Hefei WenHefei Wen, Harvard University and Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Benjamin G DrussBenjamin G. Druss, Emory University, Atlanta, Georgia.
Travis LouxTravis Loux, Saint Louis University, St. Louis, Missouri.
Kenton J JohnstonKenton J. Johnston (johnstonkj@wustl.edu), Washington University in St. Louis, St. Louis, Missouri.

Funding

Can the Medicare Quality Payment Program Incentivize Evidence-Based Treatment of Depression and Anxiety Disorders by Primary Care Providers?R01MH125820 · NIMH · WASHINGTON UNIVERSITY · PI JOHNSTON, KENTON JAMES · 2021 to 2024
$1.4M
NIMH NIH HHS R01 MH125820
6 · The paper itself

Abstract

Accountable care organizations (ACOs) have become Medicare's dominant care model because policy makers believe that ACOs will improve the quality and efficiency of care for chronic conditions. Depression and anxiety disorders are the most prevalent and undertreated chronic mental health conditions in Medicare. Yet it is unknown whether ACOs influence treatment and outcomes for these conditions. To explore these questions, this longitudinal study used data from the 2016-19 Medicare Current Beneficiary Survey, linked to validated depression and anxiety symptom instruments, among diagnosed and undiagnosed fee-for-service Medicare patients with these conditions. Among patients not enrolled in ACOs at baseline, those who newly enrolled in ACOs in the following year were 24 percent less likely to have their depression or anxiety treated during the year than patients who remained unenrolled in ACOs, and they saw no relative improvements at twelve months in their depression and anxiety symptoms. Better-designed incentives are needed to motivate Medicare ACOs to improve mental health treatment.

Indexed as

Accountable Care OrganizationsMedicareAgedAnxiety DisordersDepressionHumansLongitudinal StudiesMental HealthPatient Reported Outcome MeasuresUnited States

Identifiers

PMID37931192
PMCPMC11122701

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.